| emission_model {gtfs2emis} | R Documentation |
Emission model
Description
Estimate hot-exhaust emissions of public transport systems. This
function must be used together with transport_model.
Usage
emission_model(
tp_model,
ef_model,
fleet_data,
pollutant,
reference_year = 2020,
heightfile = NULL,
parallel = TRUE,
ncores = NULL,
output_path = NULL,
continue = FALSE,
quiet = TRUE
)
Arguments
tp_model |
sf_linestring object or a character path the to sf_linestring objects.
The |
ef_model |
character. A string indicating the emission factor model
to be used. Options include |
fleet_data |
data.frame. A |
pollutant |
character. Vector with one or more pollutants to be estimated.
Example: |
reference_year |
numeric. Year of reference considered to calculate the
emissions inventory. Defaults to |
heightfile |
character or raster data. The raster file with height data,
or its filepath, used to estimate emissions considering the effect of
street slope. This argument is used only when |
parallel |
logical. Decides whether the function should run in parallel.
Defaults is |
ncores |
integer. Number of cores to be used in parallel execution. This
argument is ignored if parallel is |
output_path |
character. File path where the function output is exported.
If |
continue |
logical. Argument that can be used only with output_path When TRUE, it skips processing the shape identifiers that were already saved into files. It is useful to continue processing a GTFS file that was stopped for some reason. Default value is FALSE. |
quiet |
Logical; Display messages from the emissions or emission factor functions. Default is 'TRUE'. |
Details
The fleet_data must be a data.frame organized according to the desired
ef_model. The required columns is organized as follows (see @examples for real
data usage).
-
reference_year: character; Base year of the emission factor model input. Required only whenef_usa_movesor_efusa_emfacare selected. -
tech: character; After treatment technology. This is required only whenemep_europeis selected. Check?ef_emep_europefor details. -
euro: character; Euro period of vehicle, classified in "Conventional", "I", "II", "III", "IV", "V", "VI", and "EEV". This is required only whenef_emep_europeis selected. Checkef_europe_emepfor details. -
fuel: character; Required whenef_usa_moves,ef_usa_emfacandef_europe_emepare selected. -
fleet_composition: Numeric. Scaled composition of fleet. In most cases, the user might not know which vehicles run on each specific routes. The composition is used to attribute a probability of a specific vehicle to circulate in the line. The probability sums one. Required for all emission factors selection. Users can check the gtfs2emis fleet data vignette, for more examples.
Based on the input height data, the function returns the slope class between two consecutive bus stop positions of a LineString Simple Feature (transport model object). The slope is given by the ratio between the height difference and network distance from two consecutive public transport stops. The function classifies the slope into one of the seven categories available on the European Environmental Agency (EEA) database, which is -0.06, -0.04,-0.02, 0.00, 0.02, 0.04, and 0.06. The classifications is described in
Value
A list with emissions estimates or NULL with output files saved
locally at output_path.
See Also
Other Core function:
transport_model()
Examples
library(gtfstools)
# read GTFS
gtfs_file <- system.file("extdata/bra_cur_gtfs.zip", package = "gtfs2emis")
gtfs <- gtfstools::read_gtfs(gtfs_file)
# keep a single trip_id to speed up this example
gtfs_small <- gtfstools::filter_by_trip_id(gtfs, trip_id ="4451136")
# run transport model
tp_model <- transport_model(gtfs_data = gtfs_small,
min_speed = 2,
max_speed = 80,
new_speed = 20,
spatial_resolution = 100,
parallel = FALSE)
# Example using Brazilian emission model and fleet
fleet_data_ef_cetesb <- data.frame(veh_type = "BUS_URBAN_D",
model_year = 2010:2019,
fuel = "D",
fleet_composition = rep(0.1,10)
)
emi_cetesb <- progressr::with_progress(emission_model(
tp_model = tp_model,
ef_model = "ef_brazil_cetesb",
fleet_data = fleet_data_ef_cetesb,
pollutant = c("CO","PM10","CO2","CH4","NOx")
))
# Example using European emission model and fleet
fleet_data_ef_europe <- data.frame( veh_type = c("Ubus Midi <=15 t",
"Ubus Std 15 - 18 t",
"Ubus Artic >18 t")
, euro = c("III","IV","V")
, fuel = rep("D",3)
, tech = c("-","SCR","SCR")
, fleet_composition = c(0.4,0.5,0.1))
emi_emep <- progressr::with_progress(emission_model(tp_model = tp_model
, ef_model = "ef_europe_emep"
, fleet_data = fleet_data_ef_europe
, pollutant = c("PM10","NOx")))
raster_cur <- system.file("extdata/bra_cur-srtm.tif", package = "gtfs2emis")
emi_emep_slope <- progressr::with_progress(emission_model(tp_model = tp_model
, ef_model = "ef_europe_emep"
, fleet_data = fleet_data_ef_europe
, heightfile = raster_cur
, pollutant = c("PM10","NOx")))
# Example using US EMFAC emission model and fleet
fleet_data_ef_moves <- data.frame( veh_type = "BUS_URBAN_D"
, model_year = 2010:2019
, fuel = "D"
, reference_year = 2020
, fleet_composition = rep(0.1,10))
fleet_data_ef_emfac <- data.frame( veh_type = "BUS_URBAN_D"
, model_year = 2010:2019
, fuel = "D"
, reference_year = 2020
, fleet_composition = rep(0.1,10))
# Example using US MOVES emission model and fleet
emi_moves <- emission_model(tp_model = tp_model
, ef_model = "ef_usa_moves"
, fleet_data = fleet_data_ef_moves
, pollutant = c("CO","PM10","CO2","CH4","NOx")
, reference_year = 2020)
emi_emfac <- emission_model(tp_model = tp_model
, ef_model = "ef_usa_emfac"
, fleet_data = fleet_data_ef_emfac
, pollutant = c("CO","PM10","CO2","CH4","NOx")
, reference_year = 2020)